Journal
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
Volume 26, Issue 3, Pages 277-292Publisher
WILEY
DOI: 10.1002/dac.1342
Keywords
aggregated multicast; minimum grouping problem; ant colony optimisation; hypothesis test; greedy algorithm
Funding
- China Next Generation Internet (CNGI), China [CNGI-04-13-2T]
- National Natural Science Foundation of China (NFSC) [60773101]
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The tree-based delivery structure of the traditional Internet protocol multicast requires each on-tree router to maintain a forwarding state for a group. This leads to a state scalability problem when large numbers of concurrent groups exist in a network. To address this state scalability problem, a novel scheme called aggregated multicast has recently been proposed, in which multiple groups are forced to share one delivery tree. In this paper, we define the aggregated multicast problem based on the minimum grouping model, and propose an ant colony optimisation algorithm. The relative fullness of the tree is defined according to the characteristics of the minimum grouping problem and is introduced as an important component in identifying the aggregation fitness function between two multicast groups. New pheromone update rules are designed based on the aggregation fitness function. To improve the convergence time of the algorithm, we use the changes (brought by each group) in the relative fullness of the current tree as the selection heuristic information. The impact of the relative fullness of the tree is analysed using the hypothesis test, and simulation results indicate that introducing relative fullness to the fitness function can significantly improve the optimisation performance of the algorithm. Compared with other heuristic algorithms, our algorithm has better optimisation performance and is more suitable for scenarios with larger bandwidth waste rates. Copyright (c) 2011 John Wiley & Sons, Ltd.
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